How IoT changes decision making, security and public policy – Erik Brynjolfsson

Professor of Information Technology, Director, The MIT Initiative on the Digital Economy


Professor of Information Technology,
Director, The MIT Initiative on the Digital Economy

We’re in the early stages of a management revolution. The upheaval is based on our unprecedented ability to collect, measure and digitally record information about human and systems activities, particularly with the finely tuned data sets available through IoT. One of the hallmarks of this new era is the acceleration of data-driven decision making within businesses, which has tripled in just five years, according to a recent study I conducted with Kristina McElheren, a professor at University of Toronto.

Accompanying the progress anticipated in this increasingly digital age, however, will be thorny challenges and broader issues for society at large. This is particularly true as organizations begin to feed the large data sets available from IoT into systems that use machine-learning algorithms—at which point they will begin making predictions and decisions in an increasingly automated way, and at large scale.

Machine-learning and artificial intelligence (AI) technologies have advanced greatly in recent years; the implications range much further than the attention they get for winning competitions with “Go” champions and chess masters. The real significance of these technologies will be found in their ability to automate and augment complex decision making.

Consider how IoT and AI-based decision making could impact retail. By instantly gathering and analyzing information from store shelves, inventory and customer purchases, large retailers could make inferences and decisions in milliseconds while benefiting from the informational economies of scale. With their detailed knowledge of customer behaviors, large retailers will operate with the customer intimacy of mom-and-pop stores, even though their headquarters are thousands of miles away.

As the premium on large, quantitative data sets grows, more companies will continue to move away from making decisions based on what they think and toward those based on what they know. Our research indicates that companies in the top third of their industry in the use of data-driven decision making are, on average, 5% more productive and 6% more profitable than competitors.

Facing Privacy Issues

The combination of IoT and AI is already starting to raise all sorts of societal issues, particularly when it comes to security and privacy. For most of human history, it was physically impossible to know very much about people’s buying habits, time use or personal lives unless you hired a private detective to follow them around. Today, that same level of insight can be gleaned through connected devices like mobile phones. As we become more digital, it isn’t the laws of physics but the laws of humans that determine who has access to information.

We have to consider whom we want to access this kind of information: law enforcement officials, marketers, the people who generate the data themselves? At one extreme, we could keep the data inaccessible to anyone at all, but this would prevent us from reaping potential benefits such as stopping crime and fighting disease, as well as more mundane benefits like better customer service and more tailored products.

Privacy issues will need to be approached from multiple angles. Governments will implement regulations, but individual organizations will often need to go beyond the letter of the law to maintain customer goodwill. As Amazon CEO Jeff Bezos said in this year’s annual letter to shareholders, there are two types of decisions—those that are reversible and those that aren’t—and it’s crucial to distinguish between the two. Any decision that affects your brand, reputation and customer trust falls into the latter category. Given how intimately IoT data is tied to people’s lives and behaviors, misusing it can have irreversible consequences, so companies will need to minimize risk when employing it.

For organizations to succeed in a time of unprecedented access to data and automated decision making, they will need to develop not just data management, AI and analytics know-how but also a sensitivity for social concerns and how these powerful capabilities impact the greater good.

Erik Brynjolfsson is Professor at the MIT Sloan School of Management and Director of the MIT Initiative on the Digital Economy.

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